Creating data in a data store using a dynamic ontology

ABSTRACT

In one embodiment, a method comprises creating and storing an ontology for a data store in response to receiving first user input defining the ontology, wherein the ontology comprises a plurality of data object types and a plurality of object property types; creating one or more parser definitions in response to receiving second user input defining the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform first input data into modified input data that is compatible with one of the object property types; and storing each of the one or more parser definitions in association with one of the plurality of object property types.

BENEFIT CLAIM

The present application claims the benefit under 35 U.S.C. § 120 as acontinuation of application Ser. No. 14/954,680, filed Nov. 30, 2015,now U.S. Pat. No. 9,589,014, which is a continuation of application Ser.No. 14/508,696, filed Oct. 7, 2014, now U.S. Pat. No. 9,201,920, whichis a continuation of application Ser. No. 13/916,447, filed Jun. 12,2013, now U.S. Pat. No. 8,856,153, which is a continuation ofapplication Ser. No. 13/106,636, filed May 12, 2011, now U.S. Pat. No.8,489,623, which is a continuation of application Ser. No. 11/602,626,filed Nov. 20, 2006, now U.S. Pat. No. 7,962,495, the entire contents ofwhich are hereby incorporated by reference for all purposes as if fullyset forth herein. The applicant(s) hereby rescind any disclaimer ofclaim scope in the parent application(s) or the prosecution historythereof and advise the USPTO that the claims in this application may bebroader than any claim in the parent application(s).

FIELD OF THE INVENTION

The present disclosure generally relates to techniques for creating datain a data store.

BACKGROUND

The approaches described in this section are approaches that could bepursued, but not necessarily approaches that have been previouslyconceived or pursued. Therefore, unless otherwise indicated, it shouldnot be assumed that any of the approaches described in this sectionqualify as prior art merely by virtue of their inclusion in thissection.

Computer-based database systems, such as relational database managementsystems, typically organize data according to a fixed structure oftables and relationships. The structure may be described using anontology, embodied in a database schema, comprising a data model that isused to represent the structure and reason about objects in thestructure.

An ontology of a database is normally fixed at the time that thedatabase is created. Any change in the ontology represented by theschema is typically extremely disruptive to the database system andrequires a database administrator to modify tables or relationships, orcreate new tables or relationships.

The rigidity of the typical database ontology is a serious drawback fororganizations that require flexible and dynamic data processingtechniques according to changes in the data that is collected. Forexample, intelligence analysis is poorly suited to conventional fixedontology systems.

SUMMARY

In one embodiment, a method comprises creating and storing an ontologyfor a data store in response to receiving first user input defining theontology, wherein the ontology comprises a plurality of data objecttypes and a plurality of object property types; creating one or moreparser definitions in response to receiving second user input definingthe parser definitions, wherein each of the parser definitions specifiesone or more sub-definitions of how to transform first input data intomodified input data that is compatible with one of the object propertytypes; storing each of the one or more parser definitions in associationwith one of the plurality of object property types; wherein themachine-executed operation is at least one of (a) sending saidinstructions over transmission media, (b) receiving said instructionsover transmission media, (c) storing said instructions onto amachine-readable storage medium, and (d) executing the instructions.

In one feature, the method further comprises receiving the first inputdata; determining whether the first input data matches one of the parsersub-definitions; using a matching one of the parser sub-definitions,creating and storing the modified input data; storing the modified inputdata in a property of the property type that is identified in thematching one of the parser sub-definitions.

In another feature, creating and storing one or more parser definitionscomprises creating and storing one or more program code modules, whereineach of the code modules comprises computer program code which whenexecuted causes transforming the first input data into the modifiedinput data.

In another feature, creating and storing one or more parser definitionscomprises creating and storing one or more transformation expressions,wherein each of the transformation expressions comprises one or moresyntactic patterns and a property type identifier associated with eachof the syntactic patterns.

In yet another feature, creating and storing one or more parserdefinitions comprises creating and storing one or more transformationexpressions, wherein each of the transformation expressions comprisesone or more syntactic patterns and a property type identifier associatedwith each of the syntactic patterns, and the method further comprisesreceiving the first input data; determining whether the first input datamatches one of the syntactic patterns; using a matching one of thesyntactic patterns, creating and storing modified input data; storingthe modified input data in a property of the property type that isidentified by the property type identifier associated with the matchingone of the syntactic patterns.

In still another feature, creating one or more parser definitionscomprises creating one or more parser definitions comprising aconstraint on what modified input data is acceptable for creation of aproperty of one of the object property types. In a further feature,creating one or more parser definitions comprises creating one or moreparser definitions comprising a default value to substitute for onecomponent of the modified input data.

In another feature, the method further comprises receiving the firstinput data; determining whether the first input data matches successivedifferent ones of the parser sub-definitions until a matching parsersub-definition is identified; using a matching one of the parsersub-definitions, creating and storing the modified input data; storingthe modified input data in a property of the property type that isidentified in the matching one of the parser sub-definitions.

According to another embodiment, a data storage system comprises a datastore; an ontology coupled to the data store and comprising a pluralityof data object types and a plurality of object property types; a parsercoupled to the ontology and configured to receive input data andtransform the input data into modified data to store in a property ofone of the property types according to one or more parser definitions;wherein each of the object property types comprises one or more of theparser definitions, wherein each of the parser definitions specifies oneor more sub-definitions of how to transform first input data intomodified input data that is compatible with one of the object propertytypes.

According to another embodiment, an apparatus comprises means forcreating and storing an ontology for a data store in response toreceiving first user input defining the ontology, wherein the ontologycomprises a plurality of data object types and a plurality of objectproperty types; means for creating one or more parser definitions inresponse to receiving second user input defining the parser definitions,wherein each of the parser definitions specifies one or moresub-definitions of how to transform first input data into modified inputdata that is compatible with one of the object property types; and meansfor storing each of the one or more parser definitions in associationwith one of the plurality of object property types.

In another embodiment, a graphical user interface comprises anexpression pattern field configured to accept user input specifying atransformation expression pattern that specifies how to transform firstinput data into modified input data; one or more parser sub-definitionseach comprising: a portion of the transformation expression pattern; acombo box configured to accept user input specifying one of a pluralityof object property component types of an ontology of a data store;wherein each of the parser sub-definitions specifies how to transform aportion of the first input data into a portion of modified input thatcan be stored in the specified component of one of the plurality ofobject property types.

In one feature, the one or more parser sub-definitions comprise aconstraint on how to transform the portion of the first input data intothe portion of modified input data that is compatible with one of theobject property types. In yet another feature, the one or more parsersub-definitions comprise a default value to substitute for the modifiedinput data if it is empty.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by wayof limitation, in the figures of the accompanying drawings and in whichlike reference numerals refer to similar elements and in which:

FIG. 1 illustrates a system for creating data in a data store using adynamic ontology;

FIG. 2 illustrates defining a dynamic ontology for use in creating datain a data store;

FIG. 3 illustrates a method of transforming data and creating the datain a data store using a dynamic ontology;

FIG. 4 illustrates an example object type editor;

FIG. 5A illustrates an example parser editor;

FIG. 5B illustrates an example property editing wizard in which multipleparsers have been created for a particular property; and

FIG. 6 illustrates a computer system with which an embodiment may beimplemented.

DESCRIPTION OF EXAMPLE EMBODIMENTS

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present invention. It will be apparent, however,that the present invention may be practiced without these specificdetails. In other instances, well-known structures and devices are shownin block diagram form in order to avoid unnecessarily obscuring thepresent invention. In an embodiment, a user of a database systemspecifies an ontology of the database in terms of object types andproperty types for properties of the objects. The user further specifieshow to parse input data for the database and how to map the parsed datainto database elements such as objects or object properties. Thedatabase is chosen as an example embodiment, other embodiments such asflat files or search indexes could be considered as well.

I. Dynamic Ontology Database System

FIG. 1 illustrates a system for creating data in a database using adynamic ontology. A parser 102 is coupled to an ontology 106, which iscoupled to a database 108. In an embodiment, ontology 106 comprisesstored information providing a data model of data stored in database108, and the ontology is defined by one or more object types 110 and oneor more property types 116. One or more objects 112 in the database 108may be instantiated based on the object types 110, and each of theobjects has one or more properties 114A, 114B that are instantiatedbased on property types 116. The property types 116 each may compriseone or more components 118, such as a string, number, etc. Propertytypes 116 may be instantiated based on a base type 120. For example, abase type 120 may be “Locations” and a property type 116 may be “Home.”

In an embodiment, a user of the system uses an object type editor 124 tocreate the object types 110 and define attributes of the object types.In an embodiment, a user of the system uses a property type editor 126to create the property types 116 and define attributes of the propertytypes.

In an embodiment, creating a property type 116 using the property typeeditor 126 involves defining at least one parser definition using aparser editor 122. A parser definition comprises metadata that informsparser 102 how to parse input data 100 to determine whether values inthe input data can be assigned to the property type 116 that isassociated with the parser definition. In an embodiment, each parserdefinition may comprise a regular expression parser 104A or a codemodule parser 104B. In other embodiments, other kinds of parserdefinitions may be provided using scripts or other programmaticelements. The elements of a regular expression parser 104A and a codemodule parser 104B are described further in subsequent sections. Oncedefined, both a regular expression parser 104A and a code module parser104B can provide input to parser 102 to control parsing of input data100.

In one embodiment of using the system of FIG. 1, input data 100 isprovided to parser 102. An object-property mapping for the input data100 enables the parser to determine which object type 110 should receivedata from a row of the input data, and which property types 116 shouldreceive data from individual field values in the input data. Based onthe object-property mapping 101, the parser 102 selects one of theparser definitions that is associated with a property type in the inputdata. The parser parses an input data field using the selected parserdefinition, resulting in creating modified data 103. The modified data103 is added to the database 108 according to ontology 106 by storingvalues of the modified data in a property of the specified propertytype. As a result, input data 100 having varying format or syntax can becreated in database 108. The ontology 106 may be modified at any timeusing object type editor 124 and property type editor 126. Parser editor122 enables creating multiple parser definitions that can successfullyparse input data 100 having varying format or syntax and determine whichproperty types should be used to transform input data 100 into modifiedinput data 103.

II. Defining a Dynamic Ontology

FIG. 2 illustrates defining a dynamic ontology for use in creating datain a database. For purposes of illustrating a clear example, steps202-209 of FIG. 2 are first described at a high level, and details of anexample implementation follow the high level description.

In step 202, one or more object types are created for a databaseontology. In step 206, one or more property types are created for eachobject type. As indicated in step 204, the attributes of object types orproperty types of the ontology may be edited or modified at any time.

In step 208, at least one parser definition is created for each propertytype. At step 209, attributes of a parser definition may be edited ormodified at any time.

In an embodiment, each property type is declared to be representative ofone or more object types. A property type is representative of an objecttype when the property type is intuitively associated with the objecttype. For example, a property type of “Social Security Number” may berepresentative of an object type “Person” but not representative of anobject type “Business.”

In an embodiment, each property type has one or more components and abase type. In an embodiment, a property type may comprise a string, adate, a number, or a composite type consisting of two or more string,date, or number elements. Thus, property types are extensible and canrepresent complex data structures. Further, a parser definition canreference a component of a complex property type as a unit or token.

An example of a property having multiple components is a Name propertyhaving a Last Name component and a First Name component. An example ofraw input data is “Smith, Jane”. An example parser definition specifiesan association of input data to object property components as follows:{LAST_NAME}, {FIRST_NAME}→Name:Last, Name:First. In an embodiment, theassociation {LAST_NAME}, {FIRST_NAME} is defined in a parser definitionusing regular expression symbology. The association {LAST_NAME},{FIRST_NAME} indicates that a last name string followed by a first namestring comprises valid input data for a property of type Name. Incontrast, input data of “Smith Jane” would not be valid for thespecified parser definition, but a user could create a second parserdefinition that does match input data of “Smith Jane”. The definitionName:Last, Name:First specifies that matching input data values map tocomponents named “Last” and “First” of the Name property.

As a result, parsing the input data using the parser definition resultsin assigning the value “Smith” to the Name:Last component of the Nameproperty, and the value “Jane” to the Name:First component of the Nameproperty.

In an embodiment, administrative users use an administrative editor tocreate or edit object types and property types. In an embodiment, usersuse the administrative editor to specify parser definitions and toassociate regular expressions, code modules or scripts with the parserdefinitions. In the administrative editor, a user can specify attributesand components of a property type. For example, in one embodiment a userspecifies a graphical user interface icon that is associated with theproperty type and displayed in a user interface for selecting theproperty type. The user further specifies a parser definition that isassociated with the property type and that can parse input data and mapthe input data to properties corresponding to the property type. Theuser further specifies a display format for the property type indicatinghow users will see properties of that property type.

FIG. 4 illustrates an example object type editor. In an embodiment, anobject type editor panel 402 comprises graphical buttons 404 forselecting add, delete, and edit functions, and one or more rows 406 thatidentify object types and a summary of selected attributes of the objecttypes. Example selected attributes that can be displayed in objecteditor panel 402 include an object type name 408 (for example,“Business”), a uniform resource identifier (URI) 410 specifying alocation of information defining the object type (for example,“com.palantir.object.business”), and a base type 412 of the object type,also expressed in URI format (for example,“com.palantir.object.entity”). Each URI also may include a graphicalicon 414.

In an embodiment, a user interacts with a computer to perform thefollowing steps to define an object type. Assume for purposes of anexample that the new object type is Vehicle. Using the object typeeditor, the user selects the “Add Object Type” button 404 and thecomputer generates and displays a panel that prompts the user to entervalues for a new object type. The user selects a base object type ofEntity, which may comprise any person, place or thing. The user assignsa graphical icon to the Vehicle object type. The user assigns a displayname of “Vehicle” to the object type.

In an embodiment, a user interacts with the computer to define aproperty type in a similar manner. The user specifies a name for theproperty type, a display name, and an icon. The user may specify one ormore validators for a property type. Each validator may comprise aregular expression that input data modified by a parser must match toconstitute valid data for that property type. In an embodiment, eachvalidator is applied to input data before a process can store themodified input data in an object property of the associated propertytype. Validators are applied after parsing and before input data isallowed to be stored in an object property.

In various embodiments, validators may comprise regular expressions, aset of fixed values, or a code module. For example, a property type thatis a number may have a validator comprising a regular expression thatmatches digits 0 to 9. As another example, a property type that is a USstate may have a validator that comprises the set {AK, AL, CA . . . VA}of valid two-letter postal abbreviations for states. Validator sets maybe extendible to allow a user to add further values. A property type mayhave component elements, and each component element may have a differentvalidator. For example, a property type of “Address” may comprise ascomponents “City”, “State”, and “ZIP”, each of which may have adifferent validator.

In an embodiment, defining a property type includes identifying one ormore associated words for the property type. The associated wordssupport search functions in large database systems. For example, aproperty type of “Address” may have an associated word of “home” so thata search in the system for “home” properties will yield “Address” as oneresult.

In an embodiment, defining a property type includes identifying adisplay formatter for the property type. A display formatter specifieshow to print or display a property type value.

In an embodiment, the parser definitions each include a regularexpression that matches valid input, and the parser uses a regularexpression processing module. For example, conventional Java languageprocessors typically have regular expression processing modules builtin. In an embodiment, parser definitions comprising regular expressionsmay be chained together. In another embodiment, one or more of theparser definitions each include a code module that contains logic forparsing input data and determining whether the input data matches aspecified syntax or data model. The code module may be written in Java,JavaScript, or any other suitable source language.

In an embodiment, there may be any number of parser definitions andsub-definitions. The number of parser definitions is unimportant becausethe input data is applied successively to each parser definition until amatch occurs. When a match occurs, the input data is mapped using theparser sub definitions to one or more components of an instance of anobject property. As a result, input data can vary syntactically from adesired syntax but correct data values are mapped into correct objectproperty values in a database.

Accordingly, referring again to FIG. 2, creating a parser definition fora property type at step 208 may comprise selecting a parser type such asa regular expression, code module, or other parser type. When the parsertype is “code module,” then a user specifies the name of a particularcode module, script, or other functional element that can performparsing for the associated property type.

In an embodiment, defining a property type includes creating adefinition of a parser for the property type using a parser editor. FIG.5A illustrates an example parser editor user interface screen display.In an embodiment, screen display 502 comprises a Parser Type combo box504 that can receive a user selection of a parser type, such as “RegularExpression” or “Code Module.” Screen display 502 further comprises aName text entry box 506 that can receive a user-specified name for theparser definition.

When the parser type is “regular expression,” steps 214-220 areperformed. At step 214, regular expression text is specified. Forexample, when the Parser Type value of combo box 504 is “RegularExpression,” screen display 502 comprises an Expression Pattern text box508 that can receive a user entry of regular expression pattern text.

In step 216, a property type component and a matching sub-definition ofregular expression text is specified. For example, screen display 502further comprises one or more property type component mappings 510. Eachproperty type component mapping associates a sub-definition of theregular expression pattern text with the property type component that isshown in a combo box 512. A user specifies a property type component byselecting a property type component using combo box 512 for anassociated sub-definition 513. As shown in step 218, specifying aproperty type component and sub-definition of regular expression textmay be repeated for all other property type components of a particularproperty type. As seen in the example of FIG. 5A, six (6) property typecomponent mappings 510 have been created for different property types(ADDRESS1, ADDRESS2, ADDRESS3, CITY, STATE, ZIP).

In step 220, a user may specify one or more constraints, default values,and/or other attributes of a parser definition. In the example of FIG.5A, the user also may specify that a match to a particular property typecomponent is not required by checking a “Not Required” check box 514.Screen display 502 may further comprise a Default Value text box 514that can receive user input for a default value for the property typecomponent. If a Default Value is specified, then the associated propertytype receives that value if no match occurs for associated grouping ofthe regular expression. In alternative embodiments, other constraintsmay be specified.

At step 222, the parser definition is stored in association with aproperty type. For example, selecting the SAVE button 520 of FIG. 5Acauses storing a parser definition based on the values entered in screendisplay 502. Parser definitions may be stored in database 108.

For purposes of illustrating a clear example, the approach of FIG. 2 hasbeen described with reference to FIG. 5A. However, the approach of FIG.2 may be implemented using other mechanisms for creating and specifyingthe values and elements identified in FIG. 2, and the particular GUI ofFIG. 5A is not required.

III. Creating Data in a Database Using a Dynamic Ontology

FIG. 3 illustrates a method of transforming data and creating the datain a database using a dynamic ontology. For purposes of illustrating aclear example, the approach of FIG. 3 is described herein with referenceto FIG. 1. However, the approach of FIG. 3 may be implemented usingother mechanisms for performing the functional steps of FIG. 3, and theparticular system of FIG. 1 is not required.

In step 302, input data is received. In an embodiment, an input datafile is received. The input data file may comprise a comma-separatedvalue (CSV) file, a spreadsheet, XML or other input data file format.Input data 100 of FIG. 1 may represent such file formats or any otherform of input data.

In step 304, an object type associated with input data rows of the inputdata is identified, and one or more property types associated with inputdata fields of the input data are identified. For example, theobject-property mapping 101 of FIG. 1 specifies that input data 100comprises rows corresponding to object type PERSON and fieldscorresponding to property type components LAST_NAME, FIRST_NAME ofproperty type NAME. The object-property mapping 101 may be integratedinto input data 100 or may be stored as metadata in association with adata input tool.

In step 306, a row of data is read from the input data, and one or morefield values are identified based on delimiters or other fieldidentifiers in the input data.

In step 308, a set of parser definitions associated with the propertytype of a particular input data field is selected. For example, metadatastored as part of creating a property type specifies a set of parserdefinitions, as previously described in connection with FIG. 5A.

In step 310, the next parser definition is applied to an input datafield value. Thus, data fields are read from each row of the file andmatched to each parser that has been defined for the correspondingproperty types. For example, assume that the mapping indicates that aninput data CSV file comprises (Last Name, First Name) values for Nameproperties of Person objects. Data fields are read from the input dataCSV file and compared to each of the parsers that has been defined forthe Name property type given the First Name field and Last Name field.If a match occurs for a (Last Name, First Name) pair value to any of theparsers for the Name property type, then the parser transforms the inputdata pair of (,Last Name, First Name) into modified input data to bestored in an instantiation of a Name property.

If applying a definition at step 310 results in a match to the inputdata, as tested at step 312, then at step 318 a property instance iscreated, and the input data field value is stored in a property of theproperty type associated with the matching sub-definition of the parserdefinition. For example, referring to FIG. 5A, assume that the inputdata matches the regular expression 508 for an ADDRESS value. Themapping 510 specifies how to store the data matching each grouping ofthe regular expression into a component of the ADDRESS property. Inresponse, an instance of an ADDRESS property is created in computermemory and the matching modified input data value is stored in eachcomponent of the property instance.

If no match occurs at step 312, then control transfers to step 314 totest whether other parser definitions match the same input data value.FIG. 5B illustrates an example property editing wizard in which multipleparsers have been created for a particular property, and through theloop shown in FIG. 3, each of the multiple parsers can be used inmatching input data. If no match occurs to the given parser definition,then any other parser definitions for that property type are matcheduntil either no match occurs, or no other parser definitions areavailable.

If a grouping is empty, then the component is filled by the defaultvalue for that component, if it exists. If no other parser definitionsare available, then control transfers from step 314 to step 316, atwhich point an error is raised or the property is discarded

At step 320, the preceding steps are repeated for all other values androws in the input data until the process has transformed all the inputdata into properties in memory.

At step 322, an object of the correct object type is instantiated. Forexample, the object-property mapping 101 may specify an object type forparticular input data, and that type of object is instantiated. Thenewly created object is associated in memory with the properties thatare already in memory. The resulting object is stored in the database instep 324.

Steps in the preceding process may be organized in a pipeline. Using theapproaches herein, a user can self-define a database ontology and useautomated, machine-based techniques to transform input data according touser-defined parsers and store the transformed data in the databaseaccording to the ontology. The approach provides efficient movement ofdata into a database according to an ontology. The input data hasimproved intelligibility after transformation because the data is storedin a canonical ontology. Further, the approach is flexible andadaptable, because the user can modify the ontology at any time and isnot tied to a fixed ontology. The user also can define multiple parsersto result in semantic matches to input data even when the syntax of theinput data is variable.

IV. Example Implementation Hardware

FIG. 6 is a block diagram that illustrates a computer system 600 uponwhich an embodiment of the invention may be implemented. Computer system600 includes a bus 602 or other communication mechanism forcommunicating information, and a processor 604 coupled with bus 602 forprocessing information. Computer system 600 also includes a main memory606, such as a random access memory (RAM) or other dynamic storagedevice, coupled to bus 602 for storing information and instructions tobe executed by processor 604. Main memory 606 also may be used forstoring temporary variables or other intermediate information duringexecution of instructions to be executed by processor 604. Computersystem 600 further includes a read only memory (ROM) 608 or other staticstorage device coupled to bus 602 for storing static information andinstructions for processor 604. A storage device 610, such as a magneticdisk or optical disk, is provided and coupled to bus 602 for storinginformation and instructions.

Computer system 600 may be coupled via bus 602 to a display 612, such asa cathode ray tube (CRT), for displaying information to a computer user.An input device 614, including alphanumeric and other keys, is coupledto bus 602 for communicating information and command selections toprocessor 604. Another type of user input device is cursor control 616,such as a mouse, a trackball, or cursor direction keys for communicatingdirection information and command selections to processor 604 and forcontrolling cursor movement on display 612. This input device typicallyhas two degrees of freedom in two axes, a first axis (e.g., x) and asecond axis (e.g., y), that allows the device to specify positions in aplane.

The invention is related to the use of computer system 600 forimplementing the techniques described herein. According to oneembodiment of the invention, those techniques are performed by computersystem 600 in response to processor 604 executing one or more sequencesof one or more instructions contained in main memory 606. Suchinstructions may be read into main memory 606 from anothermachine-readable medium, such as storage device 610. Execution of thesequences of instructions contained in main memory 606 causes processor604 to perform the process steps described herein. In alternativeembodiments, hard-wired circuitry may be used in place of or incombination with software instructions to implement the invention. Thus,embodiments of the invention are not limited to any specific combinationof hardware circuitry and software.

The term “machine-readable medium” as used herein refers to any mediumthat participates in providing data that causes a machine to operationin a specific fashion. In an embodiment implemented using computersystem 600, various machine-readable media are involved, for example, inproviding instructions to processor 604 for execution. Such a medium maytake many forms, including but not limited to, non-volatile media,volatile media, and transmission media. Non-volatile media includes, forexample, optical or magnetic disks, such as storage device 610. Volatilemedia includes dynamic memory, such as main memory 606. Transmissionmedia includes coaxial cables, copper wire and fiber optics, includingthe wires that comprise bus 602. Transmission media can also take theform of acoustic or light waves, such as those generated during radiowave and infrared data communications. All such media must be tangibleto enable the instructions carried by the media to be detected by aphysical mechanism that reads the instructions into a machine.

Common forms of machine-readable media include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, or any other magneticmedium, a CD-ROM, any other optical medium, punch cards, paper tape, anyother physical medium with patterns of holes, a RAM, a PROM, and EPROM,a FLASH-EPROM, any other memory chip or cartridge, a carrier wave asdescribed hereinafter, or any other medium from which a computer canread.

Various forms of machine-readable media may be involved in carrying oneor more sequences of one or more instructions to processor 604 forexecution. For example, the instructions may initially be carried on amagnetic disk of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 600 canreceive the data on the telephone line and use an infrared transmitterto convert the data to an infrared signal. An infrared detector canreceive the data carried in the infrared signal and appropriatecircuitry can place the data on bus 602. Bus 602 carries the data tomain memory 606, from which processor 604 retrieves and executes theinstructions. The instructions received by main memory 606 mayoptionally be stored on storage device 610 either before or afterexecution by processor 604.

Computer system 600 also includes a communication interface 618 coupledto bus 602. Communication interface 618 provides a two-way datacommunication coupling to a network link 620 that is connected to alocal network 622. For example, communication interface 618 may be anintegrated services digital network (ISDN) card or a modem to provide adata communication connection to a corresponding type of telephone line.As another example, communication interface 618 may be a local areanetwork (LAN) card to provide a data communication connection to acompatible LAN. Wireless links may also be implemented. In any suchimplementation, communication interface 618 sends and receiveselectrical, electromagnetic or optical signals that carry digital datastreams representing various types of information.

Network link 620 typically provides data communication through one ormore networks to other data devices. For example, network link 620 mayprovide a connection through local network 622 to a host computer 624 orto data equipment operated by an Internet Service Provider (ISP) 626.ISP 626 in turn provides data communication services through theworldwide packet data communication network now commonly referred to asthe “Internet” 628. Local network 622 and Internet 628 both useelectrical, electromagnetic or optical signals that carry digital datastreams. The signals through the various networks and the signals onnetwork link 620 and through communication interface 618, which carrythe digital data to and from computer system 600, are exemplary forms ofcarrier waves transporting the information.

Computer system 600 can send messages and receive data, includingprogram code, through the network(s), network link 620 and communicationinterface 618. In the Internet example, a server 630 might transmit arequested code for an application program through Internet 628, ISP 626,local network 622 and communication interface 618.

The received code may be executed by processor 604 as it is received,and/or stored in storage device 610, or other non-volatile storage forlater execution. In this manner, computer system 600 may obtainapplication code in the form of a carrier wave.

In the foregoing specification, embodiments of the invention have beendescribed with reference to numerous specific details that may vary fromimplementation to implementation. Thus, the sole and exclusive indicatorof what is the invention, and is intended by the applicants to be theinvention, is the set of claims that issue from this application, in thespecific form in which such claims issue, including any subsequentcorrection. Any definitions expressly set forth herein for termscontained in such claims shall govern the meaning of such terms as usedin the claims. Hence, no limitation, element, property, feature,advantage or attribute that is not expressly recited in a claim shouldlimit the scope of such claim in any way. The specification and drawingsare, accordingly, to be regarded in an illustrative rather than arestrictive sense.

What is claimed is:
 1. A computer-implemented method comprising: storingan ontology for a data store, wherein the ontology comprises a pluralityof data object types and a plurality of object property types;receiving, at a computing device, first user input defining one or moreparticular object types and one or more particular object property typesfor the one or more particular object types; the computing deviceupdating the ontology by creating and storing, in the ontology, the oneor more particular object types and the one or more particular objectproperty types; receiving, at the computing device, second user inputdefining one or more parser definitions for the one or more particularobject property types; wherein the one or more parser definitionscomprises one or more sub-definitions of how to transform first inputdata into modified input data that is compatible with the one or moreparticular object property types, the one or more sub-definitions beingdefined based on the second user input; the computing device updatingthe ontology by creating and storing, in the ontology, the one or moreparser definitions for the one or more particular object property types;receiving the first input data; determining that the first input datamatches the one or more parser sub-definitions; using the one or moreparser sub-definitions, creating the modified input data and storing themodified input data in a property of the object property type that isidentified in the one or more parser sub-definitions.
 2. The method ofclaim 1, wherein creating and storing one or more parser definitionscomprises creating and storing one or more program code modules, whereinthe one or more program code modules comprise computer program codewhich when executed causes transforming the first input data into themodified input data.
 3. The method of claim 1, wherein creating andstoring one or more parser definitions comprises creating and storingone or more transformation expressions, wherein the one or moretransformation expressions comprise one or more syntactic patterns and aproperty type identifier associated with the one or more syntacticpatterns.
 4. The method of claim 1, wherein creating and storing one ormore parser definitions comprises creating and storing one or moretransformation expressions, wherein the one or more transformationexpressions comprise one or more syntactic patterns and a property typeidentifier associated with the one or more syntactic patterns, andfurther comprising: receiving the first input data; determining whetherthe first input data matches the one or more syntactic patterns; using amatching of the one or more syntactic patterns, creating and storingmodified input data; storing the modified input data in a property ofthe property type that is identified by the property type identifierassociated with the matching of the one or more syntactic patterns. 5.The method of claim 1, wherein creating the one or more parserdefinitions comprises creating one or more parser definitions comprisinga constraint on the modified input data that is compatible with one ofthe object property types.
 6. The method of claim 1, wherein creatingone or more parser definitions comprises creating one or more parserdefinitions comprising a default value to substitute for a component ofthe modified input data.
 7. The method of claim 1, further comprising:using one or more transformations expressed in the sub-definition totransform portions of the input to components of the object property tocreate the modified input data; storing the modified input data in aproperty of the property type that is identified in the matching one ofthe parser sub-definitions.
 8. A system, comprising: one or moreprocessors; a data store; an ontology coupled to the data store andcomprising a plurality of data object types and a plurality of objectproperty types; one or more instructions which, when executed by the oneor more processors, cause the one or more processors to perform:receiving first user input defining one or more particular object typesand one or more particular object property types for the one or moreparticular object types; updating the ontology by creating and storing,in the ontology, the one or more particular object types and the one ormore particular object property types; receiving second user inputdefining one or more parser definitions for the one or more particularobject property types; wherein the one or more parser definitionscomprises one or more sub-definitions of how to transform first inputdata into modified input data that is compatible with the one or moreparticular object property types, the one or more sub-definitions beingdefined based on the second user input; updating the ontology bycreating and storing, in the ontology, the one or more parserdefinitions for the one or more particular object property types;receiving the first input data; determining that the first input datamatches the one or more parser sub-definitions; using the one or moreparser sub-definitions, creating the modified input data and storing themodified input data in a property of the object property type that isidentified in the one or more parser sub-definitions.
 9. The system ofclaim 8, wherein the instructions, when executed by the one or moreprocessors further cause the one or more processors to perform:receiving the first input data; determining that the first input datamatches the one or more parser sub-definitions; using the one or moreparser sub-definition, creating the modified input data; storing themodified input data in a property of the object property type that isidentified in the one or more parser sub-definitions.
 10. The system ofclaim 8, wherein the one or more parser definitions comprise one or moreprogram code modules, wherein the code modules comprises computerprogram code which when executed by the one or more processors causesthe one or more processors to perform transforming the first input datainto the modified input data.
 11. The system of claim 8, wherein the oneor more parser definitions comprise one or more transformationexpressions, wherein the one or more transformation expressions compriseone or more syntactic patterns and a property type identifier associatedwith each of the syntactic patterns.
 12. The system of claim 11 whereininstructions, when executed by the one or more processors, further causeperformance of: determining whether the first input data matches the oneor more syntactic patterns; using a matching of the one or moresyntactic patterns, creating and storing modified input data; storingthe modified input data in a property of the property type that isidentified by the property type identifier associated with the matchingof the one or more syntactic patterns.
 13. The system of claim 8,wherein creating the one or more parser definitions comprises creatingone or more parser definitions comprising a constraint on the modifiedinput data that is compatible with one of the object property types. 14.The system of claim 8, wherein creating one or more parser definitionscomprises creating one or more parser definitions comprising a defaultvalue to substitute for a component of the modified input data.
 15. Thesystem of claim 8, wherein the instructions, when executed by the one ormore processors, further cause performance of: determining whether thefirst input data matches the one or more parser sub-definitions; usingone or more transformations expressed in the sub-definition to transformportions of the input to components of the object property to create themodified input data; storing the modified input data in a property ofthe property type that is identified in the matching one of the parsersub-definitions.